activity
20242026
most citedResolving Conflicting Evidence in Automated Fact-Checking: A Study on Retrieval-Augmented LLMs

1 citations · 2 across the 7 of their papers we have counts for

collaborators

8 papers

cs.AI2026

TABVERSE: Benchmarking Cross-Format Table Understanding in LLMs and VLMs

Momina Ahsan, Sarfraz Ahmad, Ming Shan Hee +2

Large Language Models (LLMs) and Vision-Language Models (VLMs) are increasingly evaluated on table reasoning tasks, but the role of table representation remains under-explored. In…

cs.CL2025

SuperWriter: Reflection-Driven Long-Form Generation with Large Language Models

Yuhao Wu, Yushi Bai, Zhiqiang Hu +2

Long-form text generation remains a significant challenge for large language models (LLMs), particularly in maintaining coherence, ensuring logical consistency, and preserving text…

cs.CL2025

LongWriter-Zero: Mastering Ultra-Long Text Generation via Reinforcement Learning

Yuhao Wu, Yushi Bai, Zhiqiang Hu +2

Ultra-long generation by large language models (LLMs) is a widely demanded scenario, yet it remains a significant challenge due to their maximum generation length limit and overall…

cs.CL2025★ 1 cited

Resolving Conflicting Evidence in Automated Fact-Checking: A Study on Retrieval-Augmented LLMs

Ziyu Ge, Yuhao Wu, Daniel Wai Kit Chin +2

Large Language Models (LLMs) augmented with retrieval mechanisms have demonstrated significant potential in fact-checking tasks by integrating external knowledge. However, their re…

cs.CL2025

Shifting Long-Context LLMs Research from Input to Output

Yuhao Wu, Yushi Bai, Zhiqing Hu +4

Recent advancements in long-context Large Language Models (LLMs) have primarily concentrated on processing extended input contexts, resulting in significant strides in long-context…

cs.CL2025

Demystifying Hateful Content: Leveraging Large Multimodal Models for Hateful Meme Detection with Explainable Decisions

Ming Shan Hee, Roy Ka-Wei Lee

Hateful meme detection presents a significant challenge as a multimodal task due to the complexity of interpreting implicit hate messages and contextual cues within memes. Previous…

cs.CL2024★ 1 cited

Bridging Modalities: Enhancing Cross-Modality Hate Speech Detection with Few-Shot In-Context Learning

Ming Shan Hee, Aditi Kumaresan, Roy Ka-Wei Lee

The widespread presence of hate speech on the internet, including formats such as text-based tweets and vision-language memes, poses a significant challenge to digital platform saf…

cs.CL2024

LongGenBench: Benchmarking Long-Form Generation in Long Context LLMs

Yuhao Wu, Ming Shan Hee, Zhiqing Hu +1

Current benchmarks like Needle-in-a-Haystack (NIAH), Ruler, and Needlebench focus on models' ability to understand long-context input sequences but fail to capture a critical dimen…